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speech-seq2seq/wav2vec2-2-roberta-large

sourceHugging Faceupdated 5y agoView on Hugging Face
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Model Card

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This model was trained from scratch on the librispeech_asr dataset. It achieves the following results on the evaluation set:

  • —Loss: 12.2365
  • —Wer: 1.0

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • —learning_rate: 0.0001
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —gradientaccumulationsteps: 2
  • —totaltrainbatch_size: 16
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 500
  • —num_epochs: 3.0
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossWer
6.57740.2850010.54491.0
6.7060.5610009.44111.0
6.91820.84150010.95541.0
6.74161.12200010.08011.0
6.87781.425009.85691.0
6.76941.68300010.42341.0
6.74151.96350010.65451.0
6.59972.24400010.42681.0
6.76722.52450011.19291.0
6.52542.8500012.23651.0

Framework versions

  • —Transformers 4.17.0.dev0
  • —Pytorch 1.10.2+cu113
  • —Datasets 1.18.3
  • —Tokenizers 0.11.0